Bank Fundamental Score

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148

/** Deterministic TypeScript reference for D18-F10 sector-specific scoring. */

export type RecordValue = Record<string, any>;

const numberValue = (data: RecordValue, name: string): number => {
  const value = data[name];
  if (typeof value !== "number" || !Number.isFinite(value)) throw new TypeError(`${name} must be a finite number`);
  return value;
};
const nonnegative = (data: RecordValue, name: string): number => {
  const value = numberValue(data, name); if (value < 0) throw new RangeError(`${name} must be nonnegative`); return value;
};
const positive = (data: RecordValue, name: string): number => {
  const value = numberValue(data, name); if (value <= 0) throw new RangeError(`${name} must be positive`); return value;
};
const textValue = (data: RecordValue, name: string): string => {
  const value = data[name]; if (typeof value !== "string" || !value.trim()) throw new TypeError(`${name} must be a nonempty string`); return value.trim();
};
const dateValue = (value: unknown, name: string): Date => {
  if (typeof value !== "string" || !/^\d{4}-\d{2}-\d{2}$/.test(value)) throw new TypeError(`${name} must be YYYY-MM-DD`);
  const result = new Date(`${value}T00:00:00Z`); if (!Number.isFinite(result.getTime()) || result.toISOString().slice(0, 10) !== value) throw new RangeError(`${name} must be YYYY-MM-DD`); return result;
};
const requireFramework = (data: RecordValue, expected: string): void => { if (textValue(data, "framework") !== expected) throw new RangeError(`framework must be ${expected}`); };
const clamp = (value: number, low = 0, high = 100): number => Math.min(high, Math.max(low, value));
const higher = (value: number, weak: number, strong: number): number => { if (strong <= weak) throw new RangeError("strong threshold must exceed weak threshold"); return clamp(100 * (value - weak) / (strong - weak)); };
const lower = (value: number, strong: number, weak: number): number => { if (weak <= strong) throw new RangeError("weak threshold must exceed strong threshold"); return clamp(100 * (weak - value) / (weak - strong)); };
const centered = (value: number, center: number, fullDistance: number, zeroDistance: number): number => {
  if (zeroDistance <= fullDistance) throw new RangeError("zero-score distance must exceed full-score distance");
  return clamp(100 * (zeroDistance - Math.abs(value - center)) / (zeroDistance - fullDistance));
};
const weightsFor = (data: RecordValue, names: string[]): Record<string, number> => {
  const raw = data.weights;
  if (!raw || typeof raw !== "object" || Array.isArray(raw) || Object.keys(raw).sort().join("|") !== [...names].sort().join("|")) throw new RangeError("weights must contain exactly the declared component names");
  const result = Object.fromEntries(names.map(name => [name, nonnegative(raw, name)]));
  const total = Object.values(result).reduce((sum, value) => sum + value, 0);
  if (Math.abs(total - 1) > 1e-9) throw new RangeError("weights must sum to 1");
  return result;
};
const weightedScore = (components: Record<string, number>, weights: Record<string, number>): number => Object.entries(components).reduce((sum, [name, value]) => sum + value * weights[name], 0);
const scoreState = (score: number): string => score >= 75 ? "strong-review-band" : score >= 50 ? "mixed-review-band" : "weak-review-band";

function bankScore(data: RecordValue): RecordValue {
  requireFramework(data, "basel-iii-teaching-v1");
  const names = ["capital", "leverage", "short_liquidity", "stable_funding", "asset_quality", "coverage", "margin", "efficiency"];
  const weights = weightsFor(data, names);
  const values = {cet1_ratio: nonnegative(data,"cet1_ratio"), leverage_ratio: nonnegative(data,"leverage_ratio"), lcr: nonnegative(data,"lcr"), nsfr: nonnegative(data,"nsfr"), npl_ratio: nonnegative(data,"npl_ratio"), provision_coverage_ratio: nonnegative(data,"provision_coverage_ratio"), net_interest_margin: numberValue(data,"net_interest_margin"), cost_income_ratio: nonnegative(data,"cost_income_ratio")};
  const components = {capital:higher(values.cet1_ratio,.07,.14), leverage:higher(values.leverage_ratio,.03,.06), short_liquidity:higher(values.lcr,1,1.4), stable_funding:higher(values.nsfr,1,1.3), asset_quality:lower(values.npl_ratio,.02,.08), coverage:higher(values.provision_coverage_ratio,.6,1.2), margin:higher(values.net_interest_margin,.01,.04), efficiency:lower(values.cost_income_ratio,.4,.7)};
  const minimums = data.minimums; if (!minimums || typeof minimums !== "object" || Array.isArray(minimums)) throw new TypeError("minimums must be an object");
  const checks: Record<string,number> = {cet1_ratio:nonnegative(minimums,"cet1_ratio"), leverage_ratio:nonnegative(minimums,"leverage_ratio"), lcr:nonnegative(minimums,"lcr"), nsfr:nonnegative(minimums,"nsfr")};
  const breaches = Object.entries(checks).filter(([name, minimum]) => values[name as keyof typeof values] < minimum).map(([name])=>name);
  const base = weightedScore(components, weights), penalty = 12.5 * breaches.length, score = clamp(base - penalty);
  return {state:breaches.length?"prudential-floor-review":scoreState(score),method:"bank-sector-score-v1",component_scores:components,weights,base_score:base,floor_breaches:breaches,penalty,fundamental_score:score,coverage_ratio:1,reason:"package-bands-with-declared-prudential-minimums"};
}

function insuranceScore(data: RecordValue): RecordValue {
  requireFramework(data,"solvency-ii-nonlife-teaching-v1");
  const names=["solvency","minimum_capital","underwriting","reserve_quality","own_fund_quality","concentration","profitability"], weights=weightsFor(data,names);
  const values={scr_coverage_ratio:nonnegative(data,"scr_coverage_ratio"),mcr_coverage_ratio:nonnegative(data,"mcr_coverage_ratio"),combined_ratio:nonnegative(data,"combined_ratio"),adverse_reserve_development_ratio:numberValue(data,"adverse_reserve_development_ratio"),tier1_own_funds_share:nonnegative(data,"tier1_own_funds_share"),investment_concentration_ratio:nonnegative(data,"investment_concentration_ratio"),return_on_equity:numberValue(data,"return_on_equity")};
  const components={solvency:higher(values.scr_coverage_ratio,1,2),minimum_capital:higher(values.mcr_coverage_ratio,1,3),underwriting:lower(values.combined_ratio,.88,1.08),reserve_quality:lower(values.adverse_reserve_development_ratio,-.02,.08),own_fund_quality:higher(values.tier1_own_funds_share,.5,.9),concentration:lower(values.investment_concentration_ratio,.1,.4),profitability:higher(values.return_on_equity,.02,.15)};
  const breaches=["scr_coverage_ratio","mcr_coverage_ratio"].filter(name=>values[name as keyof typeof values]<1),base=weightedScore(components,weights),penalty=20*breaches.length,score=clamp(base-penalty);
  return {state:breaches.length?"capital-requirement-review":scoreState(score),method:"insurance-sector-score-v1",component_scores:components,weights,base_score:base,floor_breaches:breaches,penalty,fundamental_score:score,coverage_ratio:1,reason:"solvency-ii-tagged-nonlife-package-bands"};
}

function reitScore(data: RecordValue): RecordValue {
  requireFramework(data,"nareit-equity-reit-teaching-v1");
  const names=["distribution","leverage","coverage","occupancy","same_store_growth","liquidity"],weights=weightsFor(data,names);
  const ffo=numberValue(data,"nareit_ffo"),capex=nonnegative(data,"recurring_capex"),rent=numberValue(data,"straight_line_rent_adjustment"),dividends=positive(data,"common_dividends"),ebitda=positive(data,"ebitda_re"),interest=positive(data,"interest_expense"),nearDebt=positive(data,"near_term_debt_maturities");
  const affo=ffo-capex-rent,distribution=affo/dividends,leverage=nonnegative(data,"net_debt")/ebitda,interestCoverage=ebitda/interest,liquidity=nonnegative(data,"available_liquidity")/nearDebt;
  const components={distribution:higher(distribution,.8,1.4),leverage:lower(leverage,3.5,8),coverage:higher(interestCoverage,1.5,5),occupancy:higher(nonnegative(data,"occupancy_ratio"),.8,.97),same_store_growth:higher(numberValue(data,"same_store_noi_growth"),-.05,.08),liquidity:higher(liquidity,.75,2)};
  const score=weightedScore(components,weights);
  return {state:affo<=0?"affo-proxy-deficit-review":scoreState(score),method:"reit-sector-score-v1",nareit_ffo:ffo,affo_proxy:affo,distribution_coverage:distribution,net_debt_to_ebitda_re:leverage,interest_coverage:interestCoverage,liquidity_coverage:liquidity,component_scores:components,weights,fundamental_score:score,coverage_ratio:1,reason:"nareit-ffo-plus-explicit-package-affo-proxy"};
}

function utilityScore(data: RecordValue): RecordValue {
  requireFramework(data,"ferc-regulated-electric-teaching-v1");
  const names=["earned_return","cash_debt","capital_structure","interest_coverage","capex_funding","regulatory_lag","rate_base_growth"],weights=weightsFor(data,names);
  const allowed=positive(data,"allowed_roe"),earned=numberValue(data,"earned_roe"),debt=positive(data,"total_debt"),ffoDebt=numberValue(data,"funds_from_operations")/debt,interestCoverage=numberValue(data,"ebit")/positive(data,"interest_expense"),capexFunding=numberValue(data,"cash_from_operations")/positive(data,"capital_expenditure");
  const components={earned_return:centered(earned-allowed,0,.005,.04),cash_debt:higher(ffoDebt,.08,.22),capital_structure:lower(nonnegative(data,"debt_to_capital"),.4,.65),interest_coverage:higher(interestCoverage,1.5,5),capex_funding:higher(capexFunding,.4,1),regulatory_lag:lower(nonnegative(data,"regulatory_lag_months"),3,18),rate_base_growth:centered(numberValue(data,"rate_base_growth"),.05,.01,.08)};
  const score=weightedScore(components,weights);
  return {state:scoreState(score),method:"utility-sector-score-v1",earned_allowed_roe_gap:earned-allowed,ffo_to_debt:ffoDebt,interest_coverage:interestCoverage,capex_funding_ratio:capexFunding,component_scores:components,weights,fundamental_score:score,coverage_ratio:1,reason:"ferc-tagged-package-bands"};
}

function earlyStageScore(data: RecordValue): RecordValue {
  requireFramework(data,"early-stage-liquidity-teaching-v1");
  const names=["runway","burn_trend","obligation_cover","revenue_cover"],weights=weightsFor(data,names),cashFlows=data.monthly_net_cash_flows,revenues=data.monthly_revenue;
  if(!Array.isArray(cashFlows)||cashFlows.length<6)throw new RangeError("monthly_net_cash_flows must contain at least 6 observations");
  if(!Array.isArray(revenues)||revenues.length!==cashFlows.length)throw new RangeError("monthly_revenue must match cash-flow history");
  const flows=cashFlows.map((v:any)=>numberValue({v},"v")),revs=revenues.map((v:any)=>nonnegative({v},"v"));
  const unrestricted=nonnegative(data,"unrestricted_cash"),investments=nonnegative(data,"liquid_investments"),facility=nonnegative(data,"unconditionally_committed_facility"),obligations=nonnegative(data,"near_term_obligations"),minimumCash=nonnegative(data,"minimum_operating_cash");
  const available=unrestricted+investments+facility-obligations-minimumCash,latest=flows.slice(-6),burn=Math.max(0,-latest.reduce((a:number,b:number)=>a+b,0)/latest.length),prior=Math.max(0,-latest.slice(0,3).reduce((a:number,b:number)=>a+b,0)/3),current=Math.max(0,-latest.slice(3).reduce((a:number,b:number)=>a+b,0)/3),burnRatio=prior>0?current/prior:(current===0?0:2),gross=unrestricted+investments+facility,obligationCover=obligations>0?gross/obligations:10,latestRevenue=revs.slice(-3).reduce((a:number,b:number)=>a+b,0)/3,revenueCover=current>0?latestRevenue/current:10,runway=burn>0?available/burn:null;
  const components={runway:runway===null?100:higher(runway,6,24),burn_trend:lower(burnRatio,.75,1.25),obligation_cover:higher(obligationCover,.75,2),revenue_cover:higher(revenueCover,0,1)},score=weightedScore(components,weights);
  const state=available<0?"negative-available-liquidity":runway===null?"nonburning-observation":runway<12?"funding-window-under-12-months":scoreState(score);
  return {state,method:"early-stage-runway-score-v1",available_liquidity:available,monthly_burn:burn,prior_three_month_burn:prior,latest_three_month_burn:current,burn_ratio:burnRatio,runway_months:runway,obligation_coverage:obligationCover,revenue_to_burn:revenueCover,component_scores:components,weights,runway_score:score,coverage_ratio:1,reason:"historical-burn-sensitivity-not-management-forecast"};
}

const medianValue=(values:number[]):number=>{const sorted=[...values].sort((a,b)=>a-b),middle=Math.floor(sorted.length/2);return sorted.length%2?sorted[middle]:(sorted[middle-1]+sorted[middle])/2;};
function cyclicalScore(data:RecordValue):RecordValue{
  requireFramework(data,"cyclical-midcycle-teaching-v1");
  const names=["normalized_margin","normalized_leverage","cash_consistency","cycle_balance"],weights=weightsFor(data,names),arrays:Record<string,number[]>={};
  for(const name of ["realized_price_history","unit_cost_history","volume_history","free_cash_flow_history"]){const raw=data[name];if(!Array.isArray(raw)||raw.length<7)throw new RangeError(`${name} must contain at least 7 observations`);arrays[name]=raw.map((v:any)=>numberValue({v},"v"));}
  if(new Set(Object.values(arrays).map(v=>v.length)).size!==1)throw new RangeError("cycle histories must have equal length");
  const prices=arrays.realized_price_history,costs=arrays.unit_cost_history,volumes=arrays.volume_history;if([...prices,...costs,...volumes].some(v=>v<=0))throw new RangeError("price, cost, and volume histories must be positive");
  const normalizedPrice=medianValue(prices),normalizedCost=medianValue(costs),normalizedVolume=medianValue(volumes),revenue=normalizedPrice*normalizedVolume,ebitda=(normalizedPrice-normalizedCost)*normalizedVolume-nonnegative(data,"fixed_costs"),margin=ebitda/revenue,netDebt=nonnegative(data,"net_debt"),leverage=ebitda>0?netDebt/ebitda:null,positiveFcf=arrays.free_cash_flow_history.filter(v=>v>0).length/arrays.free_cash_flow_history.length,currentPrice=positive(data,"current_realized_price"),percentile=prices.filter(v=>v<=currentPrice).length/prices.length;
  const components={normalized_margin:higher(margin,0,.3),normalized_leverage:leverage===null?0:lower(leverage,.5,4),cash_consistency:higher(positiveFcf,.3,.9),cycle_balance:centered(percentile,.5,.1,.5)},score=weightedScore(components,weights);
  return {state:ebitda<=0?"nonpositive-midcycle-ebitda-review":scoreState(score),method:"cyclical-midcycle-normalization-v1",normalized_price:normalizedPrice,normalized_unit_cost:normalizedCost,normalized_volume:normalizedVolume,normalized_revenue:revenue,normalized_ebitda:ebitda,normalized_margin:margin,normalized_net_leverage:leverage,positive_fcf_ratio:positiveFcf,cycle_percentile:percentile,component_scores:components,weights,normalized_score:score,coverage_ratio:1,reason:"point-in-time-median-cycle-window"};
}

function holdingCompanyScore(data:RecordValue):RecordValue{
  requireFramework(data,"holding-company-lookthrough-teaching-v1");
  const names=["nav_buffer","lookthrough_leverage","parent_coverage","diversification","freshness","listed_coverage"],weights=weightsFor(data,names),holdings=data.holdings;
  if(!Array.isArray(holdings)||holdings.length<2)throw new RangeError("holdings must contain at least two records");
  const ids=new Set<string>(),rows=holdings.map((raw:any)=>{if(!raw||typeof raw!=="object"||Array.isArray(raw))throw new TypeError("each holding must be an object");const id=textValue(raw,"id");if(ids.has(id))throw new RangeError("holding IDs must be unique");ids.add(id);const ownership=numberValue(raw,"ownership_ratio");if(!(ownership>0&&ownership<=1))throw new RangeError("ownership_ratio must be in (0, 1]");if(typeof raw.listed!=="boolean"||typeof raw.stale!=="boolean")throw new TypeError("listed and stale must be booleans");return{id,ownership_ratio:ownership,attributable_equity_value:ownership*nonnegative(raw,"equity_value"),attributable_debt:ownership*nonnegative(raw,"debt"),attributable_dividends:ownership*nonnegative(raw,"dividends_to_parent"),listed:raw.listed,stale:raw.stale};});
  const parentCash=nonnegative(data,"parent_cash"),parentDebt=nonnegative(data,"parent_debt"),other=nonnegative(data,"other_parent_liabilities"),parentInterest=positive(data,"parent_interest_expense"),stake=rows.reduce((s,r)=>s+r.attributable_equity_value,0),gav=stake+parentCash;if(gav<=0)throw new RangeError("gross asset value must be positive");
  const nav=gav-parentDebt-other,attributableDebt=rows.reduce((s,r)=>s+r.attributable_debt,0),enterprise=stake+attributableDebt+parentCash,leverage=enterprise>0?(parentDebt+attributableDebt)/enterprise:1,parentCoverage=rows.reduce((s,r)=>s+r.attributable_dividends,0)/parentInterest,shares=stake>0?rows.map(r=>r.attributable_equity_value/stake):[1],concentration=shares.reduce((s,v)=>s+v*v,0),freshness=stake>0?rows.filter(r=>!r.stale).reduce((s,r)=>s+r.attributable_equity_value,0)/stake:0,listed=stake>0?rows.filter(r=>r.listed).reduce((s,r)=>s+r.attributable_equity_value,0)/stake:0,navRatio=nav/gav;
  const components={nav_buffer:higher(navRatio,.2,.8),lookthrough_leverage:lower(leverage,.2,.65),parent_coverage:higher(parentCoverage,1,4),diversification:lower(concentration,.25,.7),freshness:higher(freshness,.6,1),listed_coverage:higher(listed,.3,1)},score=weightedScore(components,weights),marketCap=data.parent_market_cap===undefined?null:nonnegative(data,"parent_market_cap"),discount=marketCap===null||nav<=0?null:1-marketCap/nav;
  return {state:nav<=0?"nonpositive-nav-review":scoreState(score),method:"holding-company-lookthrough-score-v1",holding_ledger:rows,gross_asset_value:gav,net_asset_value:nav,attributable_subsidiary_debt:attributableDebt,lookthrough_leverage:leverage,parent_interest_coverage:parentCoverage,concentration_hhi:concentration,fresh_value_coverage:freshness,listed_value_coverage:listed,discount_to_nav:discount,component_scores:components,weights,look_through_score:score,coverage_ratio:1,reason:"attributable-stakes-with-parent-bridge"};
}

const sigmoid=(value:number):number=>value>=0?1/(1+Math.exp(-value)):Math.exp(value)/(1+Math.exp(value));
const projectSimplex=(values:number[]):number[]=>{const ordered=[...values].sort((a,b)=>b-a);let cumulative=0,rho=0;ordered.forEach((value,index)=>{cumulative+=value;if(value-(cumulative-1)/(index+1)>0)rho=index+1;});const theta=(ordered.slice(0,rho).reduce((a,b)=>a+b,0)-1)/rho,projected=values.map(v=>Math.max(v-theta,0)),total=projected.reduce((a,b)=>a+b,0);return projected.map(v=>v/total);};
const brier=(rows:number[][],labels:number[],weights:number[],intercept:number,slope:number):number=>rows.reduce((sum,row,index)=>{const score=row.reduce((s,v,j)=>s+weights[j]*v,0)/100,p=sigmoid(intercept+slope*(score-.5));return sum+(p-labels[index])**2;},0)/rows.length;
function calibrateWeights(data:RecordValue):RecordValue{
  requireFramework(data,"sector-weight-calibration-teaching-v1");
  const names=data.component_names,rowsRaw=data.feature_rows,labelsRaw=data.labels,datesRaw=data.observation_dates;
  if(!Array.isArray(names)||names.length<2||new Set(names).size!==names.length||!names.every((n:any)=>typeof n==="string"&&n))throw new RangeError("component_names must be unique nonempty strings");
  if(!Array.isArray(rowsRaw)||rowsRaw.length<12)throw new RangeError("feature_rows must contain at least 12 observations");if(!Array.isArray(labelsRaw)||labelsRaw.length!==rowsRaw.length)throw new RangeError("labels must match feature_rows");if(!Array.isArray(datesRaw)||datesRaw.length!==rowsRaw.length)throw new RangeError("observation_dates must match feature_rows");
  const rows=rowsRaw.map((row:any)=>{if(!Array.isArray(row)||row.length!==names.length)throw new RangeError("each feature row must match component_names");const values=row.map((v:any)=>numberValue({v},"v"));if(values.some((v:number)=>v<0||v>100))throw new RangeError("feature scores must be within [0, 100]");return values;});
  const labels=labelsRaw.map((v:any)=>{if(v!==0&&v!==1)throw new RangeError("labels must be binary 0/1 integers");return v;});const dates=datesRaw.map((v:any)=>dateValue(v,"observation_dates"));if(dates.some((v:Date,i:number)=>i<dates.length-1&&v.getTime()>=dates[i+1].getTime()))throw new RangeError("observation_dates must be strictly increasing");
  const split=Math.trunc(numberValue(data,"train_end_index"));if(split<8||split>rows.length-4)throw new RangeError("train_end_index must leave at least 8 training and 4 validation rows");const baseMap=data.base_weights;if(!baseMap||typeof baseMap!=="object"||Array.isArray(baseMap)||Object.keys(baseMap).sort().join("|")!==[...names].sort().join("|"))throw new RangeError("base_weights must match component_names");const base=names.map((n:string)=>nonnegative(baseMap,n));if(Math.abs(base.reduce((a:number,b:number)=>a+b,0)-1)>1e-9)throw new RangeError("base_weights must sum to 1");
  const learningRate=positive(data,"learning_rate"),ridge=nonnegative(data,"ridge_penalty"),slope=positive(data,"logit_slope"),iterations=Math.trunc(positive(data,"iterations"));if(iterations>5000)throw new RangeError("iterations must not exceed 5000");let weights=[...base],intercept=0;const trainRows=rows.slice(0,split),validationRows=rows.slice(split),trainLabels=labels.slice(0,split),validationLabels=labels.slice(split);
  for(let iteration=0;iteration<iterations;iteration++){const probabilities=trainRows.map((row:number[])=>sigmoid(intercept+slope*(row.reduce((s:number,v:number,j:number)=>s+weights[j]*v,0)/100-.5))),residuals=probabilities.map((p:number,i:number)=>p-trainLabels[i]),gradIntercept=residuals.reduce((a:number,b:number)=>a+b,0)/residuals.length,gradWeights=names.map((_:string,column:number)=>residuals.reduce((sum:number,residual:number,i:number)=>sum+residual*slope*trainRows[i][column]/100,0)/trainRows.length+ridge*(weights[column]-base[column]));intercept-=learningRate*gradIntercept;weights=projectSimplex(weights.map((v:number,i:number)=>v-learningRate*gradWeights[i]));}
  const baseTrain=brier(trainRows,trainLabels,base,0,slope),baseValidation=brier(validationRows,validationLabels,base,0,slope),candidateTrain=brier(trainRows,trainLabels,weights,intercept,slope),candidateValidation=brier(validationRows,validationLabels,weights,intercept,slope),improved=candidateValidation<=baseValidation,selected=improved?weights:base,selectedIntercept=improved?intercept:0,selectedValidation=improved?candidateValidation:baseValidation;
  return {state:improved?"calibrated-improved":"retain-base-weights",method:"nonnegative-simplex-logloss-v1",component_names:names,base_weights:Object.fromEntries(names.map((n:string,i:number)=>[n,base[i]])),candidate_weights:Object.fromEntries(names.map((n:string,i:number)=>[n,weights[i]])),selected_weights:Object.fromEntries(names.map((n:string,i:number)=>[n,selected[i]])),candidate_intercept:intercept,selected_intercept:selectedIntercept,base_train_brier:baseTrain,base_validation_brier:baseValidation,candidate_train_brier:candidateTrain,candidate_validation_brier:candidateValidation,selected_validation_brier:selectedValidation,weight_shift_l1:weights.reduce((s:number,v:number,i:number)=>s+Math.abs(v-base[i]),0),train_rows:trainRows.length,validation_rows:validationRows.length,coverage_ratio:1,reason:"temporal-holdout-governs-selection"};
}

const ROUTES:Record<string,[string,string,string[]]>={bank:["D18-F10-A01","basel-iii-teaching-v1",["cet1_ratio","leverage_ratio","lcr","nsfr","npl_ratio","provision_coverage_ratio","net_interest_margin","cost_income_ratio"]],insurance:["D18-F10-A02","solvency-ii-nonlife-teaching-v1",["scr_coverage_ratio","mcr_coverage_ratio","combined_ratio","adverse_reserve_development_ratio","tier1_own_funds_share","investment_concentration_ratio","return_on_equity"]],reit:["D18-F10-A03","nareit-equity-reit-teaching-v1",["nareit_ffo","recurring_capex","common_dividends","net_debt","ebitda_re","interest_expense","occupancy_ratio","same_store_noi_growth"]],utility:["D18-F10-A04","ferc-regulated-electric-teaching-v1",["allowed_roe","earned_roe","funds_from_operations","total_debt","debt_to_capital","ebit","interest_expense","capital_expenditure"]],"early-stage":["D18-F10-A05","early-stage-liquidity-teaching-v1",["unrestricted_cash","liquid_investments","monthly_net_cash_flows","near_term_obligations"]],cyclical:["D18-F10-A06","cyclical-midcycle-teaching-v1",["realized_price_history","unit_cost_history","volume_history","free_cash_flow_history","net_debt"]],"holding-company":["D18-F10-A07","holding-company-lookthrough-teaching-v1",["holdings","parent_cash","parent_debt","parent_interest_expense"]]};
function coverageDecision(data:RecordValue):RecordValue{
  requireFramework(data,"coverage-router-teaching-v1");const sector=textValue(data,"sector"),candidate=textValue(data,"candidate_framework"),asOf=dateValue(data.as_of,"as_of"),minimum=numberValue(data,"minimum_coverage"),maxAge=Math.trunc(positive(data,"max_age_days"));if(!(minimum>0&&minimum<=1))throw new RangeError("minimum_coverage must be in (0, 1]");if(!ROUTES[sector])return{state:"abstain",method:"sector-coverage-router-v1",selected_model:null,coverage_ratio:0,available_fields:[],missing_fields:[],stale_fields:[],future_fields:[],reasons:["unsupported-sector"],reason:"unsupported-sector"};
  const [model,expected,required]=ROUTES[sector];if(candidate!==expected)return{state:"abstain",method:"sector-coverage-router-v1",selected_model:null,coverage_ratio:0,available_fields:[],missing_fields:[...required],stale_fields:[],future_fields:[],reasons:["framework-mismatch"],reason:"framework-mismatch"};const facts=data.facts;if(!Array.isArray(facts))throw new TypeError("facts must be an array");const ledger:Record<string,any>={};for(const raw of facts){if(!raw||typeof raw!=="object"||Array.isArray(raw))throw new TypeError("each fact must be an object");const name=textValue(raw,"name");if(ledger[name])throw new RangeError("fact names must be unique");if(typeof raw.value_present!=="boolean")throw new TypeError("value_present must be boolean");ledger[name]=raw;}
  const available:string[]=[],missing:string[]=[],stale:string[]=[],future:string[]=[];for(const name of required){const fact=ledger[name];if(!fact||!fact.value_present){missing.push(name);continue;}const knowledge=dateValue(fact.knowledge_date,`${name}.knowledge_date`),periodEnd=dateValue(fact.period_end,`${name}.period_end`);if(knowledge.getTime()>asOf.getTime())future.push(name);else if((asOf.getTime()-periodEnd.getTime())/86400000>maxAge)stale.push(name);else available.push(name);}const coverage=available.length/required.length,reasons:string[]=[];if(future.length)reasons.push("future-evidence");if(stale.length)reasons.push("stale-evidence");if(missing.length)reasons.push("missing-required-fields");let state:string,selected:string|null;if(future.length){state="abstain";selected=null;}else if(coverage===1){state="supported";selected=model;}else if(coverage>=minimum){state="partial-review";selected=model;}else{state="abstain";selected=null;reasons.push("coverage-below-minimum");}if(!reasons.length)reasons.push("complete-current-coverage");return{state,method:"sector-coverage-router-v1",selected_model:selected,coverage_ratio:coverage,available_fields:available,missing_fields:missing,stale_fields:stale,future_fields:future,required_field_count:required.length,reasons,reason:reasons[0]};
}

export function calculate(topicId:string,data:RecordValue):RecordValue{
  if(!data||typeof data!=="object"||Array.isArray(data))throw new TypeError("input must be an object");
  const functions:Record<string,(value:RecordValue)=>RecordValue>={"D18-F10-A01":bankScore,"D18-F10-A02":insuranceScore,"D18-F10-A03":reitScore,"D18-F10-A04":utilityScore,"D18-F10-A05":earlyStageScore,"D18-F10-A06":cyclicalScore,"D18-F10-A07":holdingCompanyScore,"D18-F10-A08":calibrateWeights,"D18-F10-A09":coverageDecision};
  if(!functions[topicId])throw new RangeError(`unsupported topic ID: ${topicId}`);return functions[topicId](data);
}